






import math
import sys

import cva
import numpy as np






def 							lowerCamelCase__ (       __lowerCamelCase     :	np.ndarray    ,						__lowerCamelCase     :	float						):
  # For applying gaussian function for each element in matrix.
  __UpperCAmelCase				:      int	 =    math.sqrt(__lowerCamelCase						)
  __UpperCAmelCase				:      Optional[Any]	 =    1 / (sigma * math.sqrt(2 * math.pi						))
  return cons * np.exp(-((img / sigma) ** 2) * 0.5						)






def 							lowerCamelCase__ (       __lowerCamelCase     :	np.ndarray    ,						__lowerCamelCase     :	int    ,						__lowerCamelCase     :	int    ,						__lowerCamelCase     :	int						):
  __UpperCAmelCase				:      List[Any]	 =    kernel_size // 2
  return img[x - half : x + half + 1, y - half : y + half + 1]






def 							lowerCamelCase__ (       __lowerCamelCase     :	int    ,						__lowerCamelCase     :	float						):
  # Creates a gaussian kernel of given dimension.
  __UpperCAmelCase				:      Union[str, Any]	 =    np.zeros((kernel_size, kernel_size)						)
  for i in range(0    ,						__lowerCamelCase						):
    for j in range(0    ,						__lowerCamelCase						):
      __UpperCAmelCase				:      str	 =    math.sqrt(
          abs(i - kernel_size // 2						) ** 2 + abs(j - kernel_size // 2						) ** 2						)
  return vec_gaussian(__lowerCamelCase    ,						__lowerCamelCase						)






def 							lowerCamelCase__ (       __lowerCamelCase     :	np.ndarray    ,						__lowerCamelCase     :	float    ,						__lowerCamelCase     :	float    ,						__lowerCamelCase     :	int    ,						):
  __UpperCAmelCase				:      Optional[Any]	 =    np.zeros(img.shape						)
  __UpperCAmelCase				:      int	 =    get_gauss_kernel(__lowerCamelCase    ,						__lowerCamelCase						)
  __UpperCAmelCase ,					__UpperCAmelCase				:      Tuple	 =    img.shape
  for i in range(kernel_size // 2    ,						size_x - kernel_size // 2						):
    for j in range(kernel_size // 2    ,						size_y - kernel_size // 2						):
      __UpperCAmelCase				:      int	 =    get_slice(__lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase    ,						__lowerCamelCase						)
      __UpperCAmelCase				:      Dict	 =    img_s - img_s[kernel_size // 2, kernel_size // 2]
      __UpperCAmelCase				:      Optional[Any]	 =    vec_gaussian(__lowerCamelCase    ,						__lowerCamelCase						)
      __UpperCAmelCase				:      Any	 =    np.multiply(__lowerCamelCase    ,						__lowerCamelCase						)
      __UpperCAmelCase				:      str	 =    np.multiply(__lowerCamelCase    ,						__lowerCamelCase						)
      __UpperCAmelCase				:      List[str]	 =    np.sum(__lowerCamelCase						) / np.sum(__lowerCamelCase						)
      __UpperCAmelCase				:      List[Any]	 =    val
  return imga






def 							lowerCamelCase__ (       __lowerCamelCase     :	list						):
  __UpperCAmelCase				:      List[str]	 =    args[1] if args[1:] else """../image_data/lena.jpg"""
  __UpperCAmelCase				:      Optional[Any]	 =    float(args[2]						) if args[2:] else 1.0
  __UpperCAmelCase				:      Dict	 =    float(args[3]						) if args[3:] else 1.0
  if args[4:]:
    __UpperCAmelCase				:      Optional[int]	 =    int(args[4]						)
    __UpperCAmelCase				:      List[str]	 =    kernel_size + abs(kernel_size % 2 - 1						)
  else:
    __UpperCAmelCase				:      int	 =    5
  return filename, spatial_variance, intensity_variance, kernel_size


if __name__ == "__main__":
       a	,a	,a	,a						:			Optional[Any]     	=					parse_args(sys.argv)
       a						:			Optional[int]     	=					cva.imread(filename, 0)
       cva.imshow("input image", img)

       a						:			int     	=					img / 255
       a						:			Union[str, Any]     	=					out.astype("float32")
       a						:			Any     	=					bilateral_filter(out, spatial_variance, intensity_variance, kernel_size)
       a						:			Optional[int]     	=					out * 255
       a						:			Union[str, Any]     	=					np.uinta(out)
       cva.imshow("output image", out)
       cva.waitKey(0)
       cva.destroyAllWindows()









'''simple docstring'''






import random
from typing import Any






def   __A    (				a_    :	list						):
		for _ in range(len(a_						)						):
				lowerCAmelCase  :     List[Any]       						= random.randint(0   ,len(a_						) - 1						)
				lowerCAmelCase  :     Tuple       						= random.randint(0   ,len(a_						) - 1						)
				lowerCAmelCase						,		lowerCAmelCase  :     Optional[Any]       						= data[b], data[a]
		return data


if __name__ == "__main__":
					lowerCAmelCase									=   [0, 1, 2, 3, 4, 5, 6, 7]
					lowerCAmelCase									=   ["""python""", """says""", """hello""", """!"""]
					print("""Fisher-Yates Shuffle:""")
					print("""List""", integers, strings)
					print("""FY Shuffle""", fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))



